Risk stratification of prostate cancer: integrating multiparametric MRI, nomograms and biomarkers
Author(s) -
Matthew J. Watson,
Arvin K. George,
Mahir Maruf,
Thomas Frye,
Akhil Muthigi,
Michael Kongnyuy,
Subin Valayil,
Peter A. Pinto
Publication year - 2016
Publication title -
future oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.857
H-Index - 72
eISSN - 1744-8301
pISSN - 1479-6694
DOI - 10.2217/fon-2016-0178
Subject(s) - nomogram , medicine , prostate cancer , multiparametric mri , prostate , disease , risk stratification , clinical practice , prostate biopsy , risk assessment , oncology , cancer , medical physics , computer security , computer science , family medicine
Accurate risk stratification of prostate cancer is achieved with a number of existing tools to ensure the identification of at-risk patients, characterization of disease aggressiveness, prediction of cancer burden and extrapolation of treatment outcomes for appropriate management of the disease. Statistical tables and nomograms using classic clinicopathological variables have long been the standard of care. However, the introduction of multiparametric MRI, along with fusion-guided targeted prostate biopsy and novel biomarkers, are being assimilated into clinical practice. The majority of studies to date present the outcomes of each in isolation. The current review offers a critical and objective assessment regarding the integration of multiparametric MRI and fusion-guided prostate biopsy with novel biomarkers and predictive nomograms in contemporary clinical practice.
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